Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study
Authors
Simon Nusinovici (ORCID: https://orcid.org/0000-0002-9599-5818)
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study
Simon Nusinovici, Zhuoting Zhu, Ten Cheer Quek, Charumathi Sabanayagam et al.
Citations
34 citations
Journal
The Lancet Healthy Longevity
Topics
Retinal Imaging and Analysis
Field-Weighted Citation Impact (FWCI)
13.75
article
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study
Simon Nusinovici, Zhuoting Zhu, Ten Cheer Quek, Charumathi Sabanayagam, Can Can Xue, Ching‐Yu Cheng, Geunyoung Lee, Mihir Deshmukh, Marco Yu, Hengtong Li, Tyler Hyungtaek Rim, Tien Yin Wong, Crystal Chun Yuen Chong, Yih Chung Tham, Emily Y. Chew, Qingsheng Peng
article en
34 citations
Abstract
No abstract available for this paper.
Publication Tag
The Lancet Healthy LongevityVol. 5(10)
Institutions
National Institutes of Health (US), Singapore National Eye Center (SG), Centre for Eye Research Australia (AU), Singapore Eye Research Institute (SG), Duke-NUS Medical School (SG), National Eye Institute (US), Guangdong Academy of Medical Sciences (CN)
Funders
Agency for Science, Technology and Research, Ministry of Trade, Industry and Energy, Korea Institute for Advancement of Technology, Medical Research Council, National Medical Research Council